China intensifies energy sector amid AI boom

Amid profound changes in the global energy landscape, deeper integration of AI and energy is seen as key to improving the resilience and efficiency of energy systems, while also carrying significance for China’s development, industrial competitiveness and energy security, experts said.

DEEP INTEGRATION

China’s National Energy Administration has rolled out a series of policy measures in recent years, providing top-level guidance that has helped drive notable progress in AI-energy integration. The country’s power sector has moved from isolated digitalization pilots to integrated development across the entire industrial chain, with power sources, grids, loads and energy storage becoming more integrated, said Yang Kun, executive vice chairman of the China Electricity Council.

According to industry data, direct investment in digitalization by China’s power sector exceeded 42 billion yuan (about 6.17 billion U.S. dollars) in 2025, ranking among the highest of all industries nationwide.

As a new factor of production, digital technologies have been rapidly integrated into power dispatching, operation and maintenance, electricity trading and equipment inspection, providing key support for the development of a new power system.

Major energy enterprises, including the State Grid Corporation of China, China Southern Power Grid and China Energy Investment Corporation, have introduced a series of large AI models, effectively improving system operational efficiency.

In the oil and gas sector, AI has been gradually applied in exploration, production, safety, environmental protection and business management, helping shift the industry from experience-based to data-driven decision-making, said Hu Senlin, vice president of the Energy Economics Institute of China National Offshore Oil Corporation.

CHALLENGES REMAIN

Despite this progress, Hu noted that deeper integration of AI and energy still faces challenges, including a shortage of industry-specific large AI models, a limited supply of high-quality industry data, and inadequate mechanisms for cross-enterprise and cross-industry data sharing.

Hu called for greater efforts to make breakthroughs in key AI technologies for the energy sector, improve industry data standards and sharing mechanisms, and promote the large-scale application of AI in the energy sector.

Meanwhile, Lyu Tingyan, deputy general manager of China Three Gorges Corporation, has warned of growing security risks as AI technologies become more deeply integrated into the energy sector. “As automation increases, machines are playing a greater role in decision-making. If systems are maliciously attacked or fed false data, the consequences could be severe,” Lyu said.

HIGH-QUALITY DEVELOPMENT

To make AI applications safer and more reliable, Guo Jianbo, an academician of the Chinese Academy of Engineering, suggested using digital twin technologies to build an intelligent “brain” for power system operations and verify AI-generated strategies.

Focusing on data infrastructure, Li Jianguo, an official with the National Data Administration, called for further exploration of technological approaches such as trusted data spaces, as well as systematic efforts to catalog multidimensional data resources related to power supply and demand, to provide a model for data circulation in the power sector.

Li said efforts will be made to promote greater coordination between computing power and electricity supply, fostering a virtuous cycle in which reliable electricity underpins computing capacity while computing technologies, in turn, enhance the power sector.

Yuan Jun, vice president of the National Data Development Research Institute, said coordinated efforts should be made in policy mechanisms, development planning, market systems and technical standards.

He also called for building an integrated resource platform covering data, computing power, electricity, AI models and applications, and pursuing technological innovation to ensure a stable power supply and more precise carbon management.